Generating Recommendations Based on Robust Term Extraction from Users' Reviews

  • Rafael Martins D D'Addio USP
  • Merley Conrado USP
  • Solange Resende USP
  • Marcelo Garcia Manzato USP

Resumo


In this paper, we propose a technique to automatically describe items based on users' reviews in order to be used by recommender systems. For that, we extract items' features using a robust term extraction method that applies transductive semi-supervised learning to automatically identify aspects that represent the different subjects of the reviews. Then, we apply sentiment analysis in a sentence level to indicate the polarities, yielding a consensus of users regarding the features of items. Our approach is evaluated using a collaborative filtering method, and comparisons using structured metadata as baselines show promising results.
Publicado
18/11/2014
D'ADDIO, Rafael Martins D; CONRADO, Merley; RESENDE, Solange; MANZATO, Marcelo Garcia. Generating Recommendations Based on Robust Term Extraction from Users' Reviews. In: BRAZILIAN SYMPOSIUM ON MULTIMEDIA AND THE WEB (WEBMEDIA), 20. , 2014, João Pessoa. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2014 . p. 55-58.

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